Noise factor analysis for cDNA microarrays

Yoganand Balagurunathan, Naisyin Wang, Edward R. Dougherty, Danh Nguyen, Yidong Chen, Michael L. Bittner, Jeffrey Trent, Raymond Carroll

Research output: Contribution to journalArticle

21 Citations (Scopus)

Abstract

A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.

Original languageEnglish (US)
Pages (from-to)663-678
Number of pages16
JournalJournal of Biomedical Optics
Volume9
Issue number4
DOIs
StatePublished - Jul 2004

Fingerprint

factor analysis
Factor analysis
Microarrays
Oligonucleotide Array Sequence Analysis
Statistical Factor Analysis
Noise
Complementary DNA
Gene expression
Degradation
gene expression
Software
simulation
degradation
computer programs
Gene Expression

Keywords

  • cDNA microarray
  • Experimental design
  • Factorial experiment
  • Image simulation
  • Signal detection

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging
  • Radiological and Ultrasound Technology
  • Clinical Biochemistry
  • Atomic and Molecular Physics, and Optics
  • Biomedical Engineering
  • Biomaterials
  • Electronic, Optical and Magnetic Materials

Cite this

Balagurunathan, Y., Wang, N., Dougherty, E. R., Nguyen, D., Chen, Y., Bittner, M. L., ... Carroll, R. (2004). Noise factor analysis for cDNA microarrays. Journal of Biomedical Optics, 9(4), 663-678. https://doi.org/10.1117/1.1755232

Noise factor analysis for cDNA microarrays. / Balagurunathan, Yoganand; Wang, Naisyin; Dougherty, Edward R.; Nguyen, Danh; Chen, Yidong; Bittner, Michael L.; Trent, Jeffrey; Carroll, Raymond.

In: Journal of Biomedical Optics, Vol. 9, No. 4, 07.2004, p. 663-678.

Research output: Contribution to journalArticle

Balagurunathan, Y, Wang, N, Dougherty, ER, Nguyen, D, Chen, Y, Bittner, ML, Trent, J & Carroll, R 2004, 'Noise factor analysis for cDNA microarrays', Journal of Biomedical Optics, vol. 9, no. 4, pp. 663-678. https://doi.org/10.1117/1.1755232
Balagurunathan Y, Wang N, Dougherty ER, Nguyen D, Chen Y, Bittner ML et al. Noise factor analysis for cDNA microarrays. Journal of Biomedical Optics. 2004 Jul;9(4):663-678. https://doi.org/10.1117/1.1755232
Balagurunathan, Yoganand ; Wang, Naisyin ; Dougherty, Edward R. ; Nguyen, Danh ; Chen, Yidong ; Bittner, Michael L. ; Trent, Jeffrey ; Carroll, Raymond. / Noise factor analysis for cDNA microarrays. In: Journal of Biomedical Optics. 2004 ; Vol. 9, No. 4. pp. 663-678.
@article{30c4f260af784ac2bdf6a2ff9f97af4b,
title = "Noise factor analysis for cDNA microarrays",
abstract = "A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.",
keywords = "cDNA microarray, Experimental design, Factorial experiment, Image simulation, Signal detection",
author = "Yoganand Balagurunathan and Naisyin Wang and Dougherty, {Edward R.} and Danh Nguyen and Yidong Chen and Bittner, {Michael L.} and Jeffrey Trent and Raymond Carroll",
year = "2004",
month = "7",
doi = "10.1117/1.1755232",
language = "English (US)",
volume = "9",
pages = "663--678",
journal = "Journal of Biomedical Optics",
issn = "1083-3668",
publisher = "SPIE",
number = "4",

}

TY - JOUR

T1 - Noise factor analysis for cDNA microarrays

AU - Balagurunathan, Yoganand

AU - Wang, Naisyin

AU - Dougherty, Edward R.

AU - Nguyen, Danh

AU - Chen, Yidong

AU - Bittner, Michael L.

AU - Trent, Jeffrey

AU - Carroll, Raymond

PY - 2004/7

Y1 - 2004/7

N2 - A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.

AB - A microarray-image model is used that takes into account many factors, including spot morphology, signal strength, background fluorescent noise, and shape and surface degradation. The model yields synthetic images whose appearance and quality reflect that of real microarray images. The model is used to link noise factors to the fidelity of signal extraction with respect to a standard image-extraction algorithm. Of particular interest is the identification of the noise factors and their interactions that significantly degrade the ability to accurately detect the true gene-expression signal. This study uses statistical criteria in conjunction with the simulation of various noise conditions to better understand the noise influence on signal extraction for cDNA microarray images. It proposes a paradigm that is implemented in software. It specifically considers certain kinds of noise in the noise model and sets these at certain levels; however, one can choose other types of noise or use different noise levels. In sum, it develops a statistical package that can work in conjunction with the existing image simulation toolbox.

KW - cDNA microarray

KW - Experimental design

KW - Factorial experiment

KW - Image simulation

KW - Signal detection

UR - http://www.scopus.com/inward/record.url?scp=4444335627&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=4444335627&partnerID=8YFLogxK

U2 - 10.1117/1.1755232

DO - 10.1117/1.1755232

M3 - Article

VL - 9

SP - 663

EP - 678

JO - Journal of Biomedical Optics

JF - Journal of Biomedical Optics

SN - 1083-3668

IS - 4

ER -